The skylark is a common bird in Northern European agricultural landscapes and has been intensively studied by scientists, with the result that its behavioural ecology is well documented. It is a useful indicator species of the effects of pesticides because of its vulnerability to agricultural practice. These features make it a key species for regulatory risk assessments but at present there is no way to fully assess the risks that pesticides pose to skylark populations. Ecological modelling offers a novel approach to this risk assessment problem. Here we ask: 1) how can real landscape sturcutre affect exposure of the population to pesticides? 2) what individual pesticide effects are the most severe in terms of population dynamics?

We developed an Individual Based Model (IBM) of the skylark using the large existing literature on the species. Currently it is deployed in a real landscape of Grange Farm near Knapwell (Cambridgeshire). This is a RSPB study area, from where we were kindly allowed to use data. Existing data is currently used to improve model parameterization using Bayesian methods. When the parameterization is finished we will systematically compare the model predictions with obsrvations reported in available studies. The performance of the model will also be compared with the more complex ALMaSS model of the Skylark developed by Dr Chris Topping of the Danish National Environmental Research Institute. An important message from previous different model type comparisons is that less complex than ABMs matrix models, though simple to run, are extraordinarily difficult to parameterize, because their parameters – birth and death rates – vary with the environment and therefore model predictions cannot be easily extrapolated.

This project runs concurrently with similar PhD projects at Reading and Syngenta modelling the behaviour of woodpigeon and small mammals. The species differ markedly in their diet, breeding and migratory strategies, but occur in the same landscapes. Thus there is value in studying the species simultaneously and in comparing them. The model has been designed and implemented in close collaboration with Katarzyna Kułakowska who works in Reading on woodpigeon model (Bird-2 project).

The project is cosupervised by a regulator, Dr M. Reed, and Dr P. Thorbek of Syngenta. Dr C.J.Topping and Dr J. D. Stark, international experts in this type of modelling, provide additional input. Outputs will be scientific papers on the model and its performance and also on the applications in pesticide exposure and effects assessment. These will make recommendations also for the level of detail that is needed in models, and for the evaluation of the effects of pesticides on populations.

The project is based in the School of Biological Sciences at the University of Reading, UK, the principal supervisor is Richard Sibly. Except of the CREAM network there is cooperation with scientists working in similar areas in Syngenta and at the UK Chemicals Regulation Directorate in York, who work on the regulatory side of pesticide risk assessment and provide insight how bird and mammal modelling would fit into risk assessment and why it is needed.

Paper by Dr. Ben Martin “Predicting population dynamics from the properties of individuals: a cross-level test of dynamic energy budget theory” was chosen to receive an Honorable Mention for the 2013 Student Paper of the Year award from The American Naturalist (i.e., one of the three best papers among 80).

On March 10th, Dr. Chun Liu spoke at the Innovation Convention 2014, in the session “Nobel inspiration: a conversation with young researchers“